[SPARK-36136][SQL][TESTS] Refactor PruneFileSourcePartitionsSuite etc…

… to a different package

### What changes were proposed in this pull request?

Move both `PruneFileSourcePartitionsSuite` and `PrunePartitionSuiteBase` to the package `org.apache.spark.sql.execution.datasources`. Did a few refactoring to enable this.

### Why are the changes needed?

Currently both `PruneFileSourcePartitionsSuite` and `PrunePartitionSuiteBase` are in package `org.apache.spark.sql.hive.execution` which doesn't look correct as these tests are not specific to Hive. Therefore, it's better to move them into `org.apache.spark.sql.execution.datasources`, the same place where the rule `PruneFileSourcePartitions` is at.

### Does this PR introduce _any_ user-facing change?

No, it's just test refactoring.

### How was this patch tested?

Using existing tests:
```
build/sbt "sql/testOnly *PruneFileSourcePartitionsSuite"
```
and
```
build/sbt "hive/testOnly *PruneHiveTablePartitionsSuite"
```

Closes #33350 from sunchao/SPARK-36136-partitions-suite.

Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>

sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/PruneFileSourcePartitionsSuite.scala → sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/PruneFileSourcePartitionsSuite.scala

@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.sql.hive.execution
+package org.apache.spark.sql.execution.datasources
 
 import org.scalatest.matchers.should.Matchers._
 
@@ -24,18 +24,19 @@ import org.apache.spark.sql.{QueryTest, Row}
 import org.apache.spark.sql.catalyst.TableIdentifier
 import org.apache.spark.sql.catalyst.dsl.expressions._
 import org.apache.spark.sql.catalyst.dsl.plans._
+import org.apache.spark.sql.catalyst.expressions.Expression
 import org.apache.spark.sql.catalyst.plans.logical.{Filter, LogicalPlan, Project}
 import org.apache.spark.sql.catalyst.rules.RuleExecutor
 import org.apache.spark.sql.execution.{FileSourceScanExec, SparkPlan}
-import org.apache.spark.sql.execution.datasources.{CatalogFileIndex, HadoopFsRelation, LogicalRelation, PruneFileSourcePartitions}
 import org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat
 import org.apache.spark.sql.execution.datasources.v2.BatchScanExec
 import org.apache.spark.sql.execution.joins.BroadcastHashJoinExec
 import org.apache.spark.sql.functions.broadcast
 import org.apache.spark.sql.internal.SQLConf
+import org.apache.spark.sql.test.SharedSparkSession
 import org.apache.spark.sql.types.StructType
 
-class PruneFileSourcePartitionsSuite extends PrunePartitionSuiteBase {
+class PruneFileSourcePartitionsSuite extends PrunePartitionSuiteBase with SharedSparkSession {
 
   override def format: String = "parquet"
 
@@ -45,35 +46,27 @@ class PruneFileSourcePartitionsSuite extends PrunePartitionSuiteBase {
 
   test("PruneFileSourcePartitions should not change the output of LogicalRelation") {
     withTable("test") {
-      withTempDir { dir =>
-        sql(
-          s"""
-            |CREATE EXTERNAL TABLE test(i int)
-            |PARTITIONED BY (p int)
-            |STORED AS parquet
-            |LOCATION '${dir.toURI}'""".stripMargin)
-
-        val tableMeta = spark.sharedState.externalCatalog.getTable("default", "test")
-        val catalogFileIndex = new CatalogFileIndex(spark, tableMeta, 0)
-
-        val dataSchema = StructType(tableMeta.schema.filterNot { f =>
-          tableMeta.partitionColumnNames.contains(f.name)
-        })
-        val relation = HadoopFsRelation(
-          location = catalogFileIndex,
-          partitionSchema = tableMeta.partitionSchema,
-          dataSchema = dataSchema,
-          bucketSpec = None,
-          fileFormat = new ParquetFileFormat(),
-          options = Map.empty)(sparkSession = spark)
-
-        val logicalRelation = LogicalRelation(relation, tableMeta)
-        val query = Project(Seq(Symbol("i"), Symbol("p")),
-          Filter(Symbol("p") === 1, logicalRelation)).analyze
-
-        val optimized = Optimize.execute(query)
-        assert(optimized.missingInput.isEmpty)
-      }
+      spark.range(10).selectExpr("id", "id % 3 as p").write.partitionBy("p").saveAsTable("test")
+      val tableMeta = spark.sharedState.externalCatalog.getTable("default", "test")
+      val catalogFileIndex = new CatalogFileIndex(spark, tableMeta, 0)
+
+      val dataSchema = StructType(tableMeta.schema.filterNot { f =>
+        tableMeta.partitionColumnNames.contains(f.name)
+      })
+      val relation = HadoopFsRelation(
+        location = catalogFileIndex,
+        partitionSchema = tableMeta.partitionSchema,
+        dataSchema = dataSchema,
+        bucketSpec = None,
+        fileFormat = new ParquetFileFormat(),
+        options = Map.empty)(sparkSession = spark)
+
+      val logicalRelation = LogicalRelation(relation, tableMeta)
+      val query = Project(Seq(Symbol("id"), Symbol("p")),
+        Filter(Symbol("p") === 1, logicalRelation)).analyze
+
+      val optimized = Optimize.execute(query)
+      assert(optimized.missingInput.isEmpty)
     }
   }
 
@@ -142,6 +135,10 @@ class PruneFileSourcePartitionsSuite extends PrunePartitionSuiteBase {
     }
   }
 
+  protected def collectPartitionFiltersFn(): PartialFunction[SparkPlan, Seq[Expression]] = {
+    case scan: FileSourceScanExec => scan.partitionFilters
+  }
+
   override def getScanExecPartitionSize(plan: SparkPlan): Long = {
     plan.collectFirst {
       case p: FileSourceScanExec => p.selectedPartitions.length

sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/PrunePartitionSuiteBase.scala → sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/PrunePartitionSuiteBase.scala

@@ -15,16 +15,15 @@
  * limitations under the License.
  */
 
-package org.apache.spark.sql.hive.execution
+package org.apache.spark.sql.execution.datasources
 
 import org.apache.spark.sql.StatisticsCollectionTestBase
 import org.apache.spark.sql.catalyst.expressions.{AttributeReference, BinaryOperator, Expression, IsNotNull, Literal}
-import org.apache.spark.sql.execution.{FileSourceScanExec, SparkPlan}
+import org.apache.spark.sql.execution.SparkPlan
 import org.apache.spark.sql.execution.datasources.v2.{BatchScanExec, FileScan}
-import org.apache.spark.sql.hive.test.TestHiveSingleton
 import org.apache.spark.sql.internal.SQLConf.ADAPTIVE_EXECUTION_ENABLED
 
-abstract class PrunePartitionSuiteBase extends StatisticsCollectionTestBase with TestHiveSingleton {
+abstract class PrunePartitionSuiteBase extends StatisticsCollectionTestBase {
 
   protected def format: String
 
@@ -95,11 +94,11 @@ abstract class PrunePartitionSuiteBase extends StatisticsCollectionTestBase with
     val plan = qe.sparkPlan
     assert(getScanExecPartitionSize(plan) == expectedPartitionCount)
 
-    val pushedDownPartitionFilters = plan.collectFirst {
-      case scan: FileSourceScanExec => scan.partitionFilters
-      case scan: HiveTableScanExec => scan.partitionPruningPred
+    val collectFn: PartialFunction[SparkPlan, Seq[Expression]] = collectPartitionFiltersFn orElse {
       case BatchScanExec(_, scan: FileScan, _) => scan.partitionFilters
-    }.map(exps => exps.filterNot(e => e.isInstanceOf[IsNotNull]))
+    }
+    val pushedDownPartitionFilters = plan.collectFirst(collectFn)
+      .map(exps => exps.filterNot(e => e.isInstanceOf[IsNotNull]))
     val pushedFilters = pushedDownPartitionFilters.map(filters => {
       filters.foldLeft("")((currentStr, exp) => {
         if (currentStr == "") {
@@ -113,5 +112,7 @@ abstract class PrunePartitionSuiteBase extends StatisticsCollectionTestBase with
     assert(pushedFilters == Some(expectedPushedDownFilters))
   }
 
+  protected def collectPartitionFiltersFn(): PartialFunction[SparkPlan, Seq[Expression]]
+
   protected def getScanExecPartitionSize(plan: SparkPlan): Long
 }

sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/PruneHiveTablePartitionsSuite.scala

@@ -18,13 +18,16 @@
 package org.apache.spark.sql.hive.execution
 
 import org.apache.spark.sql.catalyst.analysis.EliminateSubqueryAliases
+import org.apache.spark.sql.catalyst.expressions.Expression
 import org.apache.spark.sql.catalyst.plans.logical.{ColumnStat, LogicalPlan}
 import org.apache.spark.sql.catalyst.rules.RuleExecutor
 import org.apache.spark.sql.execution.SparkPlan
+import org.apache.spark.sql.execution.datasources.PrunePartitionSuiteBase
+import org.apache.spark.sql.hive.test.TestHiveSingleton
 import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types.LongType
 
-class PruneHiveTablePartitionsSuite extends PrunePartitionSuiteBase {
+class PruneHiveTablePartitionsSuite extends PrunePartitionSuiteBase with TestHiveSingleton {
 
   override def format(): String = "hive"
 
@@ -131,6 +134,10 @@ class PruneHiveTablePartitionsSuite extends PrunePartitionSuiteBase {
     }
   }
 
+  protected def collectPartitionFiltersFn(): PartialFunction[SparkPlan, Seq[Expression]] = {
+    case scan: HiveTableScanExec => scan.partitionPruningPred
+  }
+
   override def getScanExecPartitionSize(plan: SparkPlan): Long = {
     plan.collectFirst {
       case p: HiveTableScanExec => p